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Unreliable science: Unraveling the impact of mainstream media misrepresentation

2024· 1 min read ·0 comments ·0 reactions
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Unreliable science: Unraveling the impact of mainstream media misrepresentation
Authors / roleHamed Ahmadinia
Date / period1 October 2024-31 March 2026
StatusCOMPLETED
Project period1 October 2024-31 March 2026
Participants / unitsPublic-media corpus; no directly recruited human participants. The final analytical corpus contains 384 accessible online news posts from 115 news outlets referring to 46 retracted mental-health research articles. The analysis examines titles and full text, retraction awareness, citation purpose and position, author polarity, outlet characteristics, authorship and professional background, audience-engagement features, publication/retraction timing, and Altmetric-linked metadata. The study uses a mixed descriptive scientometric and interpretive content-analysis design.
MethodsDescriptive scientometrics; Interpretive content analysis; Stratified random sampling; Retraction-awareness coding; Citation & framing analysis; Pre/post-retraction comparison
Data sources384 news posts; 115 news outlets; 46 retracted mental-health articles
Project pageOpen project page

Project period: 1 October 2024-31 March 2026.

Funder: European Media and Information Fund (EMIF).

Grantee: University of Turku. Partners: University of Sheffield and OIKOPLUS GmbH.

Team leader: Senior Research Fellow Kim Holmberg. Hamed Ahmadinia’s role: Senior Researcher.

The project examines representations of retracted, corrected, low-quality and unrefereed research in mainstream and professional media, the subsequent circulation of misleading stories on social media, public awareness, and possible legal or regulatory responses.

[Un]reliable Science MOOC contribution

Hamed Ahmadinia contributed two recorded lectures to the [Un]reliable Science MOOC hosted on DigiCampus as part of this project.

Open the [Un]reliable Science MOOC information page.

Mainstream mediaMedia misrepresentationScience communicationUnreliable science
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